1. Field of the Invention
The present invention generally relates to data processing and more particularly to providing computing services through a grid computing environment.
2. Description of the Related Art
The operation of a business is a dynamic undertaking. To increase profit margins, businesses continually seek out means of assessing and controlling costs. For example, one attractive alternative to outright purchases of assets is leasing of the assets. Leasing provides flexibility and, in some cases, tax advantages.
However, regardless of whether an asset is purchased or leased, some assets have periods of idleness, or decreased usage. During these periods, the assets are not productive, or not optimally productive, but still have associated costs which the business incurs. A particular asset that suffers from this problem is the computer.
Today's computers are powerful devices having significant capacity for functions such as processing and storage. Unfortunately, the cost of owning and operating computers can be significant for some businesses. In order to be effective, the computerized resources of a business must be sufficient to meet the current needs of the business, as well as projected needs due to growth. In addition, even assuming no growth, the resources must be capable of tolerating the business's inevitable peaks and valleys of day-to-day operations due to increased loads for seasonal, period end, or special promotions.
As a result, businesses are left in the position of having to invest in more computerized resources than are immediately needed in order to accommodate growth and operational peaks and valleys. In the event the growth exceeds the available computerized resources, the business must upgrade its resources, again allowing for projected growth. Thus, at any given time in its growth cycle, a business will have excess computer capacity allowing for growth as well as the peaks and valleys of short-term operations. This excess capacity translates into real cost for the business.
One conventional solution that gives user's more flexibility is on-demand access to computerized resources. Various forms of on-demand resource access are available from International Business Machines Corporation (IBM). For example, one form of on-demand access is provided by International Business Machines, Inc. under the name “Capacity on Demand” on its line of eServer computers. In any case, computerized resources are made available on-demand in response to actual needs, rather than projected needs. In one aspect, the provision of such flexibility provides a cost efficient solution to accommodate peaks and valleys that occur in any business. Increased loads for seasonal, period end, or special promotions, for example, can be responded to quickly and efficiently. A customer pays for the capacity/resources that it needs, when it is needed. As a result, the cost of computerized resources substantially matches the computerized resources actually being used, and does not include a substantial premium for excess capacity not being used. Of course, in practice, providers may attach some form of a premium to the flexibility provided by on demand resource access. However, even with such a premium, some users will realize savings.
A problem with on-demand resources, however, is that customers may still have to incur costs associated with transportation, maintenance and storage of these additional resources. Additionally, at any given time there may be idle resources available that are not being used. This may amount to a waste of resources for a service provider and/or an unnecessary expense for a customer.
An alternative to on-demand resources is grid computing. A grid computing environment may be a type of parallel and distributed computing system which enables the sharing, selection, and aggregation of geographically distributed resources at runtime depending on their availability, capability, performance, cost, and/or user's quality of service requirements. The advantage of grid computing is that the end users are not burdened with cost of ownership issues such as purchase/lease cost and maintenance costs. However, currently users are limited in the options from which they may select when submitting requests. In particular, users are limited to specifying the minimal requirements for a job to be run properly. Examples of such requirements include the computer architecture (e.g., Intel or PowerPC), and minimal memory and disk resources.
Accordingly, there is a need for exploiting, enhancing and adding flexibilities made available to users of grid computing resources.